# Ultralytics YOLO 🚀, AGPL-3.0 license
# COCO 2017 dataset https://cocodataset.org by Microsoft
# Documentation: https://docs.ultralytics.com/datasets/detect/coco/
# Example usage: yolo train data=coco.yaml
# parent
# ├── ultralytics
# └── datasets
#     └── coco  ← downloads here (20.1 GB)

# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
path: /home/jiayuan/data/BDD_seg_mask # dataset root dir
# path: /home/jiayuan/data/yolo_v8_toy/detection-object # dataset root dir
train: images/train2017 # train images (relative to 'path') 118287 images
val: images/val2017 # val images (relative to 'path') 5000 images
test: images/val2017 # 20288 of 40670 images, submit to https://competitions.codalab.org/competitions/20794

# Classes
names:
  0: vehicle
  1: drivable
  2: lane

type_task:
  detection: [0]
  segmentation: [1, 2]